DocumentCode
3300844
Title
Some Generalized Uncertain Linguistic Aggregating Operators
Author
Wei, Guiwu
Author_Institution
Dept. of Econ. & Manage., Chongqing Univ. of Arts & Sci., Chongqing, China
fYear
2009
fDate
11-12 July 2009
Firstpage
85
Lastpage
88
Abstract
With respect to multiple attribute group decision making problem with uncertain linguistic information, in which the attribute weights and expert weights take the form of real numbers, and the attribute preference values take the form of uncertain linguistic variables, some new generalized uncertain linguistic aggregating operators have been proposed: generalized uncertain linguistic weighted aggregating (GULWA) operator, generalized uncertain linguistic ordered weighted aggregating (GULOWA) operator and generalized uncertain linguistic hybrid aggregating (GULHA) operator. It has been shown that both GULWA and GULOWA operators are the special case of the GULHA operator. The GULHA operator generalizes both the GULWA and GULOWA operators, and reflects the importance degrees of both the given arguments and their ordered positions. Based on the GULWA and GULHA operators, an approach has been proposed to solve the MAGDM problems under uncertain linguistic environment. Finally, an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness.
Keywords
computational linguistics; decision making; decision theory; mathematical operators; attribute preference value; attribute weight; expert weight; generalized uncertain linguistic ordered aggregating operator; generalized uncertain linguistic weighted aggregating operator; linguistic hybrid aggregating operator; multiple attribute group decision making problem; Art; Conference management; Decision making; Engineering management; Environmental economics;
fLanguage
English
Publisher
ieee
Conference_Titel
Services Science, Management and Engineering, 2009. SSME '09. IITA International Conference on
Conference_Location
Zhangjiajie
Print_ISBN
978-0-7695-3729-0
Type
conf
DOI
10.1109/SSME.2009.92
Filename
5233342
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